Site Reliability Engineer - Ops & Automation

Cerebras; Raleigh (NC); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Open source research

Startup vitality

Non‑corporate culture

Job summary

Cerebras Systems is seeking a hands-on SRE to own production systems and scale our AI inference services. You will collaborate with Staff SREs to build robust CD pipelines, automate capacity changes, and improve reliability through telemetry and observability across our stack.

You will bring 2–4+ years of SRE experience, production Kubernetes expertise, and proficiency in Python or Go. The role emphasizes reducing operational toil while delivering scalable, reliable systems in a fast‑growing

Qualifications

• 2–4+ years in SRE with a strong operations or automation focus.
• Production Kubernetes experience.
• Solid Python or Go for building tools and automation.
• Proficiency with Prometheus, Grafana, and observability‑driven workflows.
• Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains.

Responsibilities

• Remain hands‑on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self‑service capabilities.
• Contribute to the development of self‑service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.
• Build reusable automation and internal developer tools that minimize operational toil and cross‑team friction.
• Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale.
• Collaborate with Cluster Ops and development teams to identify high‑impact automation opportunities and iterate quickly.
• Contribute to reliability practices (SLOs, post‑mortems, capacity planning).

Skills

Kubernetes

Python

Go

Prometheus

Grafana

Observability

SRE

Tools

Argo CD

Flux

Bazel

Job description

Cerebras Systems builds the world’s largest AI chip, 56 times larger than GPUs. Its architecture delivers industry‑leading training and inference speeds—over 10 times faster than GPU‑based hyperscale cloud inference services—transforming the user experience of AI applications and enabling real‑time iteration and higher intelligence through additional agentic computation.

About The Role

We are building a high‑performance SRE function to support one of the world’s fastest‑growing AI inference services, powered by the Wafer‑Scale Engine (WSE). The role offers immediate ownership of real production systems at a growing scale, direct mentorship from seasoned engineers, and close collaboration with Staff SREs focused on long‑term automation. After roughly a month of hands‑on operations with the Staff engineers, you will primarily operate the current setup, bring up new capacity in high‑stakes environments, and help bring new continuous delivery pipelines into production use. This role does not require 24/7 on‑call rotations.

Key Responsibilities

• Remain hands‑on with operational execution (releases, capacity changes, cluster upgrades) over the next year as we build robust continuous delivery pipelines and self‑service capabilities.
• Contribute to the development of self‑service CD pipelines for key workflows using our stack: Kubernetes, Bazel, Prometheus/Grafana/InfluxDB, Python, and Go.
• Build reusable automation and internal developer tools that minimize operational toil and cross‑team friction.
• Develop and extend telemetry, observability and alerting solutions to ensure operational reliability at scale.
• Collaborate with Cluster Ops and development teams to identify high‑impact automation opportunities and iterate quickly.
• Contribute to reliability practices (SLOs, post‑mortems, capacity planning).

Required Experience & Skills

• 2–4+ years in SRE with a strong operations or automation focus.
• Production Kubernetes experience.
• Solid Python or Go for building tools and automation.
• Proficiency with Prometheus, Grafana, and observability‑driven workflows.
• Ability to measure and communicate impact – reliability metrics, operational toil, velocity gains.

Nice‑to‑Have

• Hands‑on GitOps expertise (Argo CD / Flux or equivalent) is a plus.
• Experience building continuous delivery pipelines is a strong plus.
• Experience with Bazel or similar build systems is a strong plus.
• Familiarity with capacity planning and on‑prem or multi‑datacenter environments.

Location

• SF Bay Area
• Toronto

Why Join Cerebras

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source cutting‑edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Enjoy job stability with startup vitality.
• Our simple, non‑corporate work culture that respects individual beliefs.

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.